3 papers
hep-ph2026
Pretrained Event Classification Model for High Energy Physics Analysis
Joshua Ho, Benjamin Ryan Roberts, Shuo Han +1
We introduce a foundation model for event classification in high-energy physics, built on a Graph Neural Network architecture and trained on 120 million simulated proton-proton col…
physics.data-an2025
Automating High Energy Physics Data Analysis with LLM-Powered Agents
Eli Gendreau-Distler, Joshua Ho, Dongwon Kim +3
We present a proof-of-principle study demonstrating the use of large language model (LLM) agents to automate a representative high energy physics (HEP) analysis. Using the Higgs bo…
physics.data-an2025
Transforming Simulation to Data Without Pairing
Eli Gendreau-Distler, Luc Le Pottier, Haichen Wang
We explore a generative machine learning-based approach for estimating multi-dimensional probability density functions (PDFs) in a target sample using a statistically independent b…